Clinical Decision Support Tool to Assess Risk and Prevent Agitation Events

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PROJECT SUMMARY/ABSTRACT This award is a four-year plan to support Ambrose Wong, MD, MSEd, an emergency physician, in his transition towards an independent research career that focuses on dissemination and implementation of services for mental health crises in general, non-psychiatric emergency settings. The long-term goal of his research is to improve safety related to symptoms of agitation. To date, Dr. Wong's training has focused on emergency medicine, qualitative methods, and education-based interventions. Under a team of co-mentors with expertise in biostatistics, psychiatric services research, health informatics, and clinical trial implementation, Dr. Wong will build on his preliminary work on agitation prevention and management to accomplish the following training goals: (1) acquire expertise in clinical prediction modeling, (2) gain foundational knowledge in preventing, treating, and investigating mental health crises, (3) study health informatics and development of clinical support tools, and (4) obtain fundamental skills in clinical trials. The application integrates formal coursework and training through mentored research activities. Behavioral conditions in acute care settings are rapidly rising in the U.S., with a 50% increase in number of general emergency department (ED) visits for mental health conditions over the past decade. Agitation, defined as excessive psychomotor activity leading to violent behavior, is often part of these patient encounters. Of the 1.7 million agitation episodes occurring annually in general EDs, 83% are associated with an underlying serious mental illness. Given the safety risks of agitation, clinicians commonly use physical restraint, which are associated with up to 37% risk of complications including traumatic injuries and even sudden death in patients. Thus, regulatory bodies and experts emphasize early risk assessment and use of behavioral techniques before agitation occurs. However, variability in practice and policy of these techniques exists in emergency settings. This is due to lack of knowledge regarding specific risk factors that predict the need for pre-emptive intervention and challenges in assessing these risk factors in the busy environment of an ED. The objective of this project is to develop and test the Early Detection and Treatment to Reduce Events with Agitation Tool (ED- TREAT), a clinical decision support system embedded in the electronic health record that will guide clinicians in early risk assessment and appropriate treatment of mental health patients likely to develop agitation. We will first derive a clinical model using health record data and preliminary analyses by our team that predicts which at-risk patients will develop agitation and require use of physical restraint. Next, we will develop and refine ED- TREAT through user-centered design techniques with clinicians and patients. Finally, we will conduct a pilot trial to test the feasibility, fidelity, and bedside acceptability of ED-TREAT. Aligned with NIMH's strategic priorities to use technology for improving mental health delivery in non-specialty settings, this study will form the basis for a subsequent full-scale clinical trial to examine ED-TREAT's effect on clinical outcomes.